Aspirin and other non-steroidal inflammatory drugs (NSAIDs) reduce the recurrence of colorectal polyps among patients with familial adenomatous polyposis (FAP) and are associated with a lower risk of both adenoma and colorectal cancer. Primary targets for these drugs are cyclooxygenases (COX1 and COX2) in the prostaglandin (PG) pathway. The goal of this study is to evaluate the association between colorectal polyps and polymorphisms in enzymes, growth factors, and receptors linked to prostaglandin synthesis or COX activity. Currently, very few polymorphisms in this pathway have been reported, and, of those, the population allele frequency is not known. Thus, several steps in this proposal (Projects 1-3) aim to systematically identify new genetic polymorphisms in this pathway, and to establish allele frequency and potential impact on enzyme function. Methods include screening of enzymes in the COX/PG pathway for new polymorphisms both by searching genetic databases and by using other techniques (dHPLC, enzyme mismatch cleavage, DNA sequencing). Genotyping of a population of 75 Caucasians and 75 African Americans for candidate polymorphisms will be used to establish allele frequency. Subsequently (Project 4) we propose to investigate a selected 5 to 10 genetic polymorphisms in COX1,COX2, and other enzymes in the PG/COX pathway, or growth factors and receptors related to it, and their association with colorectal polyps. We propose to genotype 550 cases with adenomatous polyps, 200 cases with hyperplastic polyps only, and 700 polyp-free controls. Study participants were recruited as part of the Minnesota case-control study in 1991-4 and comprehensive questionnaire information on health status, family history, diet, physical activity, and use of aspirin and other NSAIDs has been obtained. We will 1) investigate the main effects of the genetic polymorphisms, and 2) investigate whether these polymorphisms modify the association between environmental factors (in particular aspirin and NSAID use) and colorectal polyps. Finally, we plan to develop a model for integrating information on genetic variability at multiple points in this metabolic pathway.